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Django-google-optimize is a reusable Django application for retrieving the current experiment variant.

Project description

Django-google-optimize

Build status Coverage Supported Python versions PyPI Version

Django-google-optimize is a reusable Django application designed to make running server side Google Optimize A/B test easy.

Installation

Install django-google-optimize with pip:

pip install django-google-optimize

Add the application to installed django applications:

DJANGO_APPS = [
    ...
    "google_optimize",
    ...
]

Add the context processor:

"context_processors": [
    ...
    "google_optimize.context_processors.google_experiment",
    ...
]

Getting started

Add settings for the experiments:

  • id: Experiment ID required to identify variants for the experiment in templates
  • alias: Alias for the experiment ID, optional useful for clarity in templates when accessing experiment variants by key
  • variant_aliases: Aliases for each variant, each index represents a Optmize Experiment variant
# google-optimize
GOOGLE_OPTIMIZE_EXPERIMENTS = [
    {
        "id": "utSuKi3PRbmxeG08en8VNw",
        "alias": "redesign",
        "variant_aliases": {0: "old_design", 1: "new_design"},
    }
]

Now you can access the experiment in templates:

{% if google_optimize.redesign == "new_design" %}
{% include "jobs/jobposting_list_new.html" %}
{% else %}
{% include "jobs/jobposting_list_old.html" %}
{% endif %}

Or use it inline:

<nav class="navbar navbar-expand-lg navbar-dark
{% if google_optimize.redesign == "new_design" %} navbar-redesign{% endif %}">

Full documentation can be found here.

Documentation and Support

More documentation can be found in the docs directory or read online. Open a Github issue for support.

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Source Distribution

django-google-optimize-0.1.3.tar.gz (4.7 kB view hashes)

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django_google_optimize-0.1.3-py3-none-any.whl (4.6 kB view hashes)

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